Skip to search formSkip to main contentSkip to account menu

MNIST database

Known as: MNIST, MNIST dataset 
The MNIST database (Mixed National Institute of Standards and Technology database) is a large database of handwritten digits that is commonly used… 
Wikipedia (opens in a new tab)

Related topics

Related topics

21 relations

Broader (1)

Artificial intelligence
Artificial neural networkCaltech 101Computer performanceComputer vision

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2020
2020
Unsupervised Competitive Hardware Learning Rule for Spintronic Clustering Architecture
We propose a hardware learning rule for unsupervised clustering within a novel spintronic computing architecture. The proposed… 
Review
2019
Review
2019
Test Metrics for Recurrent Neural Networks
Recurrent neural networks (RNNs) have been applied to a broad range of application areas such as natural language processing… 
2018
2018
DropBack: Continuous Pruning During Training
We introduce a technique that compresses deep neural networks both during and after training by constraining the total number of… 
2018
2018
Solving Approximate Wasserstein GANs to Stationarity
Generative Adversarial Networks (GANs) are one of the most practical strategies to learn data distributions. A popular GAN… 
2017
2017
Design space exploration of Convolutional Neural Networks based on Evolutionary Algorithms
This paper proposes a framework for design space exploration of Convolutional Neural Networks (CNNs) using Genetic Algorithms… 
2017
2017
A Novel Two-stage Learning Pipeline for Deep Neural Networks
In this work, a training method was proposed for Deep Neural Networks (DNNs) based on a two-stage structure. Local DNN models are… 
2016
2016
Finding a good initial configuration of parameters for restricted Boltzmann machine pre-training
Restricted Boltzmann machines (RBMs) have been successfully applied in unsupervised learning and image density-based modeling… 
2016
2016
Doubly random parallel stochastic methods for large scale learning
We consider learning problems over training sets in which both, the number of training examples and the dimension of the feature… 
2016
2016
Evolutionary Synthesis of Deep Neural Networks via Synaptic Cluster-driven Genetic Encoding
There has been significant recent interest towards achieving highly efficient deep neural network architectures. A promising… 
2007
2007
Comparison and Combination of State-of-the-art Techniques for Handwritten Character Recognition: Topping the MNIST Benchmark
Although the recognition of isolated handwritten digits has been a research topic for many years, it continues to be of interest… 
By clicking accept or continuing to use the site, you agree to the terms outlined in our Privacy Policy (opens in a new tab), Terms of Service (opens in a new tab), and Dataset License (opens in a new tab)